'''simple docstring'''




from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__UpperCAmelCase					=logging.get_logger(__name__)

__UpperCAmelCase					={
    "facebook/xlm-roberta-xl": "https://huggingface.co/facebook/xlm-roberta-xl/resolve/main/config.json",
    "facebook/xlm-roberta-xxl": "https://huggingface.co/facebook/xlm-roberta-xxl/resolve/main/config.json",
    # See all XLM-RoBERTa-XL models at https://huggingface.co/models?filter=xlm-roberta-xl
}




class        a__ (  UpperCAmelCase__					):
     lowerCamelCase    :	Optional[int]				="xlm-roberta-xl"






     def __init__(					self						:						Any    ,							a						:						Union[str, Any]=25_08_80    ,							a						:						int=25_60    ,							a						:						List[Any]=36    ,							a						:						Optional[int]=32    ,							a						:						Any=1_02_40    ,							a						:						List[str]="gelu"    ,							a						:						Tuple=0.1    ,							a						:						List[str]=0.1    ,							a						:						Optional[int]=5_14    ,							a						:						List[Any]=1    ,							a						:						int=0.02    ,							a						:						Any=1e-0_5    ,							a						:						List[Any]=1    ,							a						:						Any=0    ,							a						:						str=2    ,							a						:						Optional[int]="absolute"    ,							a						:						str=True    ,							a						:						Tuple=None    ,							**a						:						Tuple    ,							):





         """simple docstring"""



         super().__init__(pad_token_id=a    ,							bos_token_id=a    ,							eos_token_id=a    ,							**a       )
         __lowerCamelCase            =    vocab_size
         __lowerCamelCase            =    hidden_size
         __lowerCamelCase            =    num_hidden_layers
         __lowerCamelCase            =    num_attention_heads
         __lowerCamelCase            =    hidden_act
         __lowerCamelCase            =    intermediate_size
         __lowerCamelCase            =    hidden_dropout_prob
         __lowerCamelCase            =    attention_probs_dropout_prob
         __lowerCamelCase            =    max_position_embeddings
         __lowerCamelCase            =    type_vocab_size
         __lowerCamelCase            =    initializer_range
         __lowerCamelCase            =    layer_norm_eps
         __lowerCamelCase            =    position_embedding_type
         __lowerCamelCase            =    use_cache
         __lowerCamelCase            =    classifier_dropout




class        a__ (  UpperCAmelCase__					):






     @property
     def   SCREAMING_SNAKE_CASE__  (					self						:						List[Any]       ):





         """simple docstring"""



         if self.task == "multiple-choice":
             __lowerCamelCase            =    {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
         else:
             __lowerCamelCase            =    {0: '''batch''', 1: '''sequence'''}
         return OrderedDict(
             [
                 ('''input_ids''', dynamic_axis),
                 ('''attention_mask''', dynamic_axis),
             ]       )

'''simple docstring'''




def __lowerCAmelCase					(				UpperCamelCase__							)      ->       float:
    __lowerCamelCase            =    0
    while len(UpperCamelCase__							) > 1:
        __lowerCamelCase            =    0
        # Consider two files with minimum cost to be merged
        for _ in range(2							):
            __lowerCamelCase            =    files.index(min(UpperCamelCase__							)							)
            temp += files[min_index]
            files.pop(UpperCamelCase__							)
        files.append(UpperCamelCase__							)
        optimal_merge_cost += temp
    return optimal_merge_cost


if __name__ == "__main__":
  import doctest

  doctest.testmod()
